In the scenario of frequency coexistence between the geostationary (GEO) and non-
geostationary (NGEO) satellite networks, the NGEO system should not incur harmful …

Recently, an origin fully-decoupled radio access network (FD-RAN) inspired by
neurotransmission has been proposed for B5G/6G mobile communication networks, which …

The eigenvalues of the sample covariance matrix can capture signal correlations and noise
characteristics well, which are widely used for spectrum sensing in cognitive radio networks …

Hybrid interweave-underlay spectrum access in cognitive radio networks can explore
spectrum opportunities when primary users (PUs) are either active or inactive, which …

Spectrum sensing is an essential problem in cognitive radio and has been discussed a lot in
recent years. In this paper, a cooperative sensing algorithm based on unsupervised learning …

This paper focuses on the design of the optimal or near-optimal detector resorting to extreme
eigenvalues. A general framework for detector design involving model-driven and data …

Cognitive radio is proposed for efficient utilization of radio spectrum using dynamic spectrum
allocation. Most of the spectrum sensing algorithms for cognitive radio are based on some …

Due to the stochastic nature of wireless channels, the received radio signal is noised during
transmission causing difficulty in classifying radio modulation categories. Deep learning …

Recently, sub-Nyquist sampling (SNS) based wideband spectrum sensing has emerged as
a promising approach for cognitive radios. However, most of existing SNS-based …

Specific emitter identification (SEI) is an effective Internet of things (IoT) data flow protection
technique of identifying individual emitters via unique characteristics of different emitters …